Logistic Regression मॉडल प्रशिक्षण

# Split the data into training and testing
train_samples,test_samples = samples.____([0.8, 0.2])

# Train the model
model = LogisticRegressionWithLBFGS.train(____)

# Create a prediction label from the test data
predictions = model.____(test_samples.map(lambda x: x.features))

# Combine original labels with the predicted labels
labels_and_preds = test_samples.map(lambda x: x.label).zip(____)

# Check the accuracy of the model on the test data
accuracy = labels_and_preds.filter(lambda x: x[0] == x[____]).count() / float(test_samples.count())
print("Model accuracy : {:.2f}".format(____))